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Transcriptomic and epigenomic analysis of neuronal differentiation models of Kabuki Syndrome Type 1 [RNA-Seq]

GSE289159 Homo sapiens (human) RNA-seq (gene expression) 23 samples Submitted 2025/09/11 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 23 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
23 samples: 6 conditions, mostly in triplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Epigenome and transcriptome changes in KMT2D-related Kabuki syndrome Type 1 iPSCs, neuronal progenitors and cortical neuronsPLoS genetics · 2025
Summary (written by the submitters)
Kabuki syndrome type 1 (KS1) is a neurodevelopmental disorder caused by loss-of-function variants in KMT2D which encodes a H3K4 methyltransferase. Here, we analysed transcriptomic differences across three stages of neuronal differentiation using patient-derived induced pluripotent stem cells (iPSCs). Overall, we identified hundreds of differentially expressed genes (DEGs) in iPSCs, NPs and CNs in KS1.
Read the full summary ↓
We find that genes regulated by SUZ12, a subunit of Polycomb Repressive complex 2, are over-represented in KS1 DEGs at early stages of differentiation. We also identify loss of thousands of H3K4me1 peaks in iPSCs, neuronal progenitors (NPs) and early cortical neurons (CNs) in KS1. In conclusion, we present a disease-relevant human cellular model for KS1 that provides pathomechanistic insights of Kabuki Syndrome Type 1.
Published in
Epigenome and transcriptome changes in KMT2D-related Kabuki syndrome Type 1 iPSCs, neuronal progenitors and cortical neurons
Cuvertino S, Martirosian E, Bhosale K et al. · PLoS genetics 2025 · PMID 40971994 · doi:10.1371/journal.pgen.1011608
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE289159_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1221827 and SRA study SRP563023. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in triplicate
iPSC, Control, ×3 iPSC, Kabuki Syndrome 1, ×3 Neuronal progenitor, Control, ×3 Neuronal progenitor, Kabuki Syndrome 1, ×3 Cortical neuron, Kabuki Syndrome 1, ×3 Cortical neuron, Control, ×2 Neuronal progenitor, Control, rep1, validatio… ×1 Neuronal progenitor, Control, rep2, validatio… ×1 +4 more

Supports a between-group comparison across 17 samples.

How we read this: 6 replicated groups read from 23 sample titles; they account for 17 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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